Multi-sensor strategy for heart failure patient management

ABSTRACT

An apparatus comprises plurality of sensors and a processor. Each sensor provides a sensor signal that includes physiological information and at least one sensor is implantable. The processor includes a physiological change event detection module that detects a physiological change event from a sensor signal and produces an indication of occurrence of one or more detected physiological change events, and a heart failure (HF) detection module. The HF detection module determines, using a first rule, whether the detected physiological change event indicative of a change in HF status of a subject, determines whether to override the first rule HF determination using a second rules, and declares whether the change in HF status occurred according to the first and second rules.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. application Ser. No.14/857,161, filed on Sep. 17, 2015, now issued as U.S. Pat. No.9,622,665, which is a continuation of U.S. application Ser. No.14/248,949, filed on Apr. 9, 2014, now issued as U.S. Pat. No.9,161,698, which is a continuation of U.S. application Ser. No.12/576,453, filed on Oct. 9, 2009, now issued as U.S. Pat. No.8,738,119, which claims the benefit of priority under 35 U.S.C. § 119(e)to U.S. Provisional Application Ser. No. 61/104,648, filed Oct. 10,2008, under 35 U.S.C. § 119(e), each of which is incorporated herein byreference in its entirety.

BACKGROUND

Implantable medical devices (IMDs) include devices designed to beimplanted into a patient or subject. Some examples of these devicesinclude cardiac function management (CFM) devices such as implantablepacemakers, implantable cardioverter defibrillators (ICDs), cardiacresynchronization therapy devices (CRTs), and devices that include acombination of such capabilities. The devices can be used to treatpatients using electrical or other therapies, or to aid a physician orcaregiver in patient diagnosis through internal monitoring of apatient's condition. The devices may include one or more electrodes incommunication with one or more sense amplifiers to monitor electricalheart activity within a patient, and often include one or more sensorsto monitor one or more other patient parameters. Other examples ofimplantable medical devices include implantable diagnostic devices,implantable drug delivery systems, or implantable devices with neuralstimulation capability.

Additionally, some IMDs detect events by monitoring electrical heartactivity signals. Some IMDs derive measurements of hemodynamicparameters related to chamber filling and contractions from electricalsignals provided by sensors. Sometimes patients who receive IMDs haveexperienced repeated heart failure (HF) decompensation or other eventsassociated with worsening HF. Symptoms associated with worsening HFinclude pulmonary and/or peripheral edema, dilated cardiomyapathy, orventricular dilation. Early attention to signs and symptoms of HFdecompensation is needed for the health of the patient and allows earlyinitiation of treatment.

OVERVIEW

This document relates generally to systems, devices, and methods formonitoring hemodynamic parameters of a patient or subject. In example 1,an apparatus comprises a plurality of sensors and a processor. Eachsensor provides a sensor signal that includes physiological informationand at least one sensor is implantable. The processor includes aphysiological change event detection module that detects a physiologicalchange event from a sensor signal and produces an indication ofoccurrence of one or more detected physiological change events, and aheart failure (HF) detection module. The HF detection module determines,using a first rule, whether the detected physiological change event isindicative of a change in HF status of a subject, determines whether tooverride the first rule HF determination using a second rule, anddeclares whether the change in HF status occurred according to the firstand second rules.

In example 2, the first rule of example 1 optionally includes indicatingthe change in HF status when a majority of a set of detectablephysiological change events is detected.

In example 3, the second rule of examples 1 and 2 optionally includesoverriding a negative first rule HF determination according to thespecificity of a detected physiological change event.

In example 4, the second rule of examples 1-3, optionally includesoverriding a negative first rule HF determination when a condition foran S3 heart sound is met in a heart sound signal.

In example 5, the second rule of examples 1-4 optionally includesoverriding a positive first rule HF determination according to anegative predictive value of a physiological change event.

In example 6, the second rule of examples 1-5 optionally includesoverriding a positive first rule HF determination when a condition in aphysiologic response to patient activity is met.

In example 7, the HF detection module of examples 1-6 optionally weightsthe second rule HF determination greater than the first ruledetermination.

In example 8, the physiological change event detection module ofexamples 1-7 is optionally configured to weight the detectedphysiological according to the sensor signal, and the HF detectionmodule is optionally configured to determine a likelihood that thechange in HF status occurred using the weight of the physiologicalchange event, and provide an alert based on the declared HF event,wherein the alert includes an indication of the likelihood that thechange in HF status occurred.

In example 9, the HF detection module of examples 1-8 is optionallyconfigured to determine a level of urgency of the alert according to thefirst and second rules.

In example 10, the plurality of sensors of examples 1-9 optionallyincludes at least one of an implantable heart sound sensor, animplantable impedance sensor, an implantable activity sensor, animplantable respiration sensor, an implantable blood pressure sensor, animplantable electrocardiogram sensor, an implantable oxygen saturationsensor, an implantable blood flow sensor, an implantable temperaturesensor; and an implantable intra-thoracic total impedance (ITTI) sensor.

In example 11, a system comprises a plurality of sensors, an implantabledevice, and an external device. Each of the sensors is configured toprovide a sensor signal that includes physiological information. Theimplantable device comprises at least one of the sensors, a samplingcircuit, communicatively coupled to the implantable sensors, configuredto provide a sampled sensor signal, and a first communication circuit,communicatively coupled to the sampling circuit, configured tocommunicate the sampled sensor signal to a second device. The externaldevice comprises a second communication circuit configured tocommunicate with the implantable device, and a processor,communicatively coupled to the second communication circuit. Theprocessor includes a physiological change event detection moduleconfigured to detect a physiological change event from a sensor signalincluding at least one sampled sensor signal communicated from theimplantable device, and produce an indication of occurrence of one ormore physiological change events. The processor also includes a heartfailure (HF) detection module configured to determine whether thedetected physiological change events are indicative of a change in HFstatus using a first rule, determine whether to override the first ruleHF determination using a second rule, and declare whether the change inHF status occurred according to the first and second rules.

In example 12, the first rule of example 11 optionally includesindicating a change in HF status when a majority of a set of detectablephysiological change events is detected. In example 13, the second ruleof examples 11 and 12 optionally includes overriding a negative firstrule HF determination according to the specificity of a detectedphysiological change event, and overriding a positive first rule HFdetermination according to a negative predictive value of aphysiological change event.

In example 14, a method includes sensing a plurality of physiologicsensor signals using a medical device where each sensor signal includesunique physiological information, and wherein at least one sensor isimplantable, detecting which physiological change events, if any, of aset of specified physiological change events occurred using the sensorsignals, determining whether the detected physiological change eventsare indicative of a change in HF status of a subject using a first rule,determining whether to override the first rule HF determination using asecond rule, and declaring whether the change in HF status occurredaccording to the first and second rules.

In example 15, the determining whether the detected physiological changeevents are indicative of a change in HF status using a first rule ofexample 15 optionally includes determining that the detectedphysiological change events are indicative of the change in HF statuswhen a number of detected physiological change events are a majority ofa set of physiological change events that indicate the change in HFstatus and are detectable by the medical device.

In example 16, the determining whether to override the first rule HFdetermination using a second rule of examples 14 and 15 optionallyincludes overriding a negative first rule HF determination according toa specificity of a detected physiological change event.

In example 17, the determining whether to override the first rule HFdetermination using a second rule of examples 14-16 optionally includesoverriding the negative first rule HF determination when a condition foran S3 heart sound is met in a heart sound signal.

In example 18, the determining whether to override the first rule HFdetermination using a second rule of examples 14-17 optionally includesoverriding a positive first rule HF determination according to anegative predictive value of a detected physiological change event.

In example 19, the determining whether to override the first rule HFdetermination using a second rule of examples 14-18 optionally includesoverriding a positive first rule HF determination when a condition in aphysiologic response to patient activity is met.

In example 20, the determining whether to override the first rule HFdetermination using a second rule of examples 14-19 optionally includesweighting the second rule HF determination greater than the first ruleHF determination.

In example 21, the determining which physiological change eventsoccurred of examples 14-20 optionally includes weighting the detectedphysiological change event according to the sensor signal, and whereinthe method includes providing an alert based on the declared change inHF status, wherein the alert includes an indication of a likelihood thatthe change in HF status occurred.

In example 22, the method of example 21 optionally includes determininga level of urgency of the alert according to the first and second rules.

In example 23, the sensing a plurality of physiological sensor signalsof examples 14-22 optionally includes sensing at least one of animplantable heart sound sensor, an implantable impedance sensor, animplantable activity sensor, an implantable respiration sensor, animplantable blood pressure sensor, an implantable electrocardiogramsensor, an implantable oxygen saturation sensor, an implantable bloodflow sensor, an implantable temperature sensor, and an implantableintra-thoracic total impedance (ITTI) sensor.

In example 24, the method of examples 14-23 optionally includes samplingat least one physiological sensor signal using an implantable device,communicating the sampled physiological sensor signal from theimplantable device to an external device, and optionally includes usingthe external device to detect a physiological change event from thesampled signal, determine whether a detected event is indicative of achange in HF status, and declare whether the change in HF statusoccurred according to the first and second rules.

This section is intended to provide an overview of subject matter of thepresent patent application. It is not intended to provide an exclusiveor exhaustive explanation of the invention. The detailed description isincluded to provide further information about the present patentapplication.

BRIEF DESCRIPTION OF THE DRAWINGS

In the drawings, which are not necessarily drawn to scale, like numeralsmay describe similar components in different views. Like numerals havingdifferent letter suffixes may represent different instances of similarcomponents. The drawings illustrate generally, by way of example, butnot by way of limitation, various embodiments discussed in the presentdocument.

FIG. 1 is an illustration of portions of a system that uses an IMD.

FIG. 2 is a block diagram of an example of a device to monitor HF of asubject.

FIG. 3 shows a flow diagram of a method to monitor HF of a subject.

FIG. 4 is a flow diagram of an example of a method to determine whethera change occurred in the status of HF of a subject.

FIG. 5 is a flow diagram of an example of another method to determinewhether a change occurred in the status of HF of a subject.

FIG. 6 is an illustration of a system that includes an external deviceused to program parameters of an IMD.

FIG. 7 is an example of a system to monitor for HF of a subject.

DETAILED DESCRIPTION

An implantable medical device (IMD) may include one or more of thefeatures, structures, methods, or combinations thereof described herein.For example, a cardiac monitor or a cardiac stimulator may beimplemented to include one or more of the advantageous features orprocesses described below. It is intended that such a monitor,stimulator, or other implantable or partially implantable device neednot include all of the features described herein, but may be implementedto include selected features that provide for unique structures orfunctionality. Such a device may be implemented to provide a variety oftherapeutic or diagnostic functions. It would be desirable for an IMD toprovide monitoring of HF in patients who have experienced HF or are atrisk of developing HF.

FIG. 1 is an illustration of portions of a system 100 that uses an IMD105. Examples of IMD 105 include, without limitation, a pacemaker, acardioverter, a defibrillator, a cardiac resynchronization therapy (CRT)device, and other cardiac monitoring and therapy delivery devices,including cardiac devices that include or work in coordination with oneor more neuro-stimulating devices, drugs, drug delivery systems, orother therapies. As one example, the system 100 shown is used to treat acardiac arrhythmia. The IMD 105 typically includes an electronics unitcoupled by one or more cardiac leads 110, 115, 125, to a heart of apatient or subject. The electronics unit of the IMD 105 typicallyincludes components that are enclosed in a hermetically-sealed canisteror “can.” The system 100 also typically includes an IMD programmer orother external system 190 that communicates one or more wireless signals185 with the IMD 105, such as by using radio frequency (RF) or by one ormore other telemetry methods.

The example shown includes right atrial (RA) lead 110 having a proximalend 111 and a distal end 113. The proximal end 111 is coupled to aheader connector 107 of the IMD 105. The distal end 113 is configuredfor placement in the RA in or near the atrial septum. The RA lead 110may include a pair of bipolar electrodes, such as an RA tip electrode114A and an RA ring electrode 114B. The RA electrodes 114A and 114B areincorporated into the lead body at distal end 113 for placement in ornear the RA, and are each electrically coupled to IMD 105 through aconductor extending within the lead body. The RA lead is shown placed inthe atrial septum, but the RA lead may be placed in or near the atrialappendage, the atrial free wall, or elsewhere.

The example shown also includes a right ventricular (RV) lead 115 havinga proximal end 117 and a distal end 119. The proximal end 117 is coupledto a header connector 107. The distal end 119 is configured forplacement in the RV. The RV lead 115 may include one or more of aproximal defibrillation electrode 116, a distal defibrillation electrode118, an RV tip electrode 120A, and an RV ring electrode 120B. Thedefibrillation electrode 116 is generally incorporated into the leadbody such as in a location suitable for supraventricular placement inthe RA and/or the superior vena cava. The defibrillation electrode 118is incorporated into the lead body near the distal end 119 such as forplacement in the RV. The RV electrodes 120A and 120B may form a bipolarelectrode pair and are generally incorporated into the lead body atdistal end 119. The electrodes 116, 118, 120A, and 120B are eachelectrically coupled to IMD 105, such as through one or more conductorsextending within the lead body. The proximal defibrillation electrode116, distal defibrillation electrode 118, or an electrode formed on thecan of IMD 105 allow for delivery of cardioversion or defibrillationpulses to the heart.

The RV tip electrode 120A, RV ring electrode 120B, or an electrodeformed on the can of IMD 105 allow for sensing an RV electrogram signalrepresentative of RV depolarizations and delivering RV pacing pulses. Insome examples, the IMD includes a sense amplifier circuit to provideamplification and/or filtering of the sensed signal. RA tip electrode114A, RA ring electrode 114B, or an electrode formed on the can of IMD105 allow for sensing an RA electrogram signal representative of RAdepolarizations and allow for delivering RA pacing pulses. Sensing andpacing allows the IMD 105 to adjust timing of the heart chambercontractions. In some examples, the IMD 105 can adjust the timing ofventricular depolarizations with respect to the timing of atrialdepolarizations by sensing electrical signals in the RA and pacing theRV at the desired atrial-ventricular (AV) delay time.

A left ventricular (LV) lead 125 can include a coronary pacing orsensing lead that includes an elongate lead body having a proximal end121 and a distal end 123. The proximal end 121 is coupled to a headerconnector 107. A distal end 123 is configured for placement or insertionin the coronary vein. The LV lead 125 may include an LV tip electrode128A and an LV ring electrode 128B. The distal portion of the LV lead125 is configured for placement in the coronary sinus and coronary veinsuch that the LV electrodes 128A and 128B are placed in the coronaryvein. The LV electrodes 128A and 128B may form a bipolar electrode pairand are typically incorporated into the lead body at distal end 123.Each can be electrically coupled to IMD 105 such as through one or moreconductors extending within the lead body. LV tip electrode 128A, LVring electrode 128B, or an electrode formed on the can of the IMD 105allow for sensing an LV electrogram signal representative of LVdepolarizations and delivering LV pacing pulses.

The IMDs may be configured with a variety of electrode arrangements,including transvenous, epicardial electrodes (i.e., intrathoracicelectrodes), and/or subcutaneous, non-intrathoracic electrodes,including can, header, and indifferent electrodes, and subcutaneousarray or lead electrodes (i.e., non-intrathoracic electrodes). Some IMDsare able to sense signals representative of cardiac depolarizationsusing electrodes without leads.

As discussed previously, early attention to signs and symptoms of HFdecompensation is needed for optimal health of the patient. One of thechallenges in detection of a change in status of HF (e.g., worsening) isto reduce false alarms while ensuring that actual or true changes instatus are detected accurately. The systems and methods described belowmonitor the patient and generate alerts to the clinician when animpending HF event is detected. Because the alerts require a clinician'stimely review of patient-related information to determine what triggeredthe alert and to identify the appropriate response, false alarms causethe unnecessary expenditure of healthcare resources. Additionally, toomany false alarms may cause the clinician to ignore all alerts as“nuisance alarms” including detections which are true, thereby defeatingthe benefit of the system.

FIG. 2 is a block diagram of an example of a device 200 to monitor HF ofa patient or subject. The device 200 includes a processor 205 and aplurality of sensors 210 communicatively coupled to the processor 205.At least one of the sensors 210 is an implantable sensor. The processor205 may include a microprocessor, a digital signal processor,application specific integrated circuit (ASIC), microprocessor, or othertype of processor, interpreting or executing instructions in software orfirmware. Each of the sensors 210 provides a sensor signal that includesphysiological information. The communicative coupling allows theprocessor 205 and the sensors 210 to communicate even though there maybe intervening circuitry between the processor 205 and the sensors 210.

In some examples, the sensors 210 include an implantable heart soundsensor. Heart sounds are associated with mechanical vibrations fromactivity of a patient's heart and the flow of blood through the heart.Heart sounds recur with each cardiac cycle and are separated andclassified according to the activity associated with the vibration. Thefirst heart sound (S1) is the vibrational sound made by the heart duringtensing of the mitral valve. The second heart sound (S2) marks theclosing of the aortic valve and the beginning of diastole. The thirdheart sound (S3) and fourth heart sound (S4) are related to fillingpressures of the left ventricle during diastole. A heart sound sensorproduces an electrical signal which is representative of mechanicalactivity of a patient's heart. The heart sound sensor is disposed in aheart, near the heart, or in another location where the acoustic energycan be sensed. In some examples, the heart sound sensor includes anaccelerometer disposed in or near a heart. In another example, the heartsound sensor includes an accelerometer disposed in the IMD. In anotherexample, the heart sound sensor includes a microphone disposed in ornear a heart.

Many types of physiological information can be included in a signalprovided by a heart sound sensor. For example, the presence of an S3heart sound may be an indication of elevated filling pressure. Thus, thedevelopment of, or a change in, an S3 heart sound may indicate a changein status of HF of the subject. An approach for monitoring heart soundsis found in Siejko et al., U.S. Patent Application Publ. No.2004/0127792, entitled “Method and Apparatus for Monitoring of DiastolicHemodynamics,” filed Dec. 30, 2002, which is incorporated herein byreference in its entirety.

In some examples, the sensors 210 include a respiration sensor. Anexample of an implantable respiration sensor is an intra-thoracic totalimpedance sensor ITTI. The signal provided by the ITTI sensor providesphysiological information that can be used to measure respirationparameters such as respiratory rate, tidal volume, minute respirationvolume, and derived parameters such as the ratio of respiratory rateover tidal volume. An approach to measuring thoracic impedance isdescribed in Hartley et al., U.S. Pat. No. 6,076,015, “Rate AdaptiveCardiac Rhythm Management Device Using Transthoracic Impedance,” filedFeb. 27, 1998, which is incorporated herein by reference in itsentirety. Measuring respiration parameters can be useful in detectingabnormal breathing.

The sensor signal provided by an ITTI sensor can also provideinformation related to a change in fluid build-up in the thorax regionof the subject. A decrease in impedance may indicate an increase ininterstitial fluid build-up due to pulmonary edema.

In some examples, the sensors 210 include an implantable patientactivity sensor. An example of an implantable patient activity sensor isan accelerometer. The combination of a respiration sensor and anactivity sensor, and/or the combination of a heart rate sensor and anactivity sensor, is useful for monitoring a patient's physiologicalresponse to activity (PRA), such as to detect one or both of abnormalbreathing and abnormal reflex sympathetic activation due to activity.The device 200 may include other types of sensors, such as thosediscussed later in this document.

The processor 205 includes a physiological change event detection module215. Modules can be software, hardware, firmware or any combinationthereof. Multiple functions can be performed in one or more modules asdesired. The physiological change event detection module 215 detects aphysiological change event from a sensor signal. A physiological changeevent refers to a detected change in subject physiology. In certainexamples, the physiological change event detection module 215 detectselevated filling pressure from a heart sound sensor signal. In certainexamples, the physiological change event detection module 215 detectsthoracic fluid from an ITTI sensor signal. In certain examples, thephysiological change event detection module 215 detects a change inheart rate using an electrocardiogram sensor. In certain examples, thephysiological change event detection module 215 detects abnormalbreathing such as tachypnea, rapid shallow breathing, apnea, hypopnea,or hyperventilation from a respiration sensor signal. In certainexamples, the physiological change event detection module 215 detectsone or both of abnormal breathing and abnormal reflex sympatheticactivation during patient activity using a respiration sensor signal, anelectrocardiographic signal, and a patient activity sensor signal. Thephysiological change event detection module 215 also produces anindication of occurrence of one or more detected physiological changeevents.

The processor 205 includes a heart failure (HF) detection module 220.The HF detection module 220 determines whether the detectedphysiological change event is indicative of a change in HF status of thepatient. To make the determination, the HF detection module 220 includesa sensor fusion algorithm used to blend the indications from thephysiological change event detection module 215. The algorithm includesapplication of two rules. The HF detection module 220 declares whetherthe change in HF status occurred according to the first and secondrules.

The first rule is applied to the detected physiological change events todetermine whether they are indicative of a change in HF status of asubject. In some examples, the HF detection module 220 makes anindividual assessment of HF from the information received from eachsensor. In some examples, the first rule includes a majority rule andindicates a change in patient HF status when detecting a majority of aset of detectable physiological change events that indicate HF (e.g.,more events are detected that are indicative HF than are events thateither are not indicative of HF or are contraindicative of HF).

The second rule determines whether to override the first rule HFdetermination. In some examples, the second rule includes overriding anegative first rule HF determination according to the specificity of adetected physiological change event. For example, application of thefirst rule may indicate no change in HF status of the patient. However,one of the sensors may provide such a strong indication of HF that thefirst rule HF determination should be overridden. An example of a strongindication of a change in HF status is development of an S3 heart soundthat previously was not present. The second rule may override thenegative first rule HF determination when a condition for an S3 heartsound is met in the heart sound sensor signal. In certain examples, theHF detection module 220 weights the second rule HF determination greaterthan the first rule HF determination to cause the override or to inhibitthe override. This provides a method of gradation of the possibleoverriding events.

In some examples, the second rule includes overriding a positive firstrule HF determination according to a negative predictive value of aphysiological change event. For example, application of the first rulemay indicate a change in HF status of the patient, but one of thesensors may provide a strong indication that no change in statusoccurred and the first rule HF determination should be overridden. Anexample of a strong indication of no change in HF status is when acondition in a physiologic response to patient activity is met, such aswhen a heart rate sensor (e.g., an implantable electrocardiogram sensor)indicates that a patient's heart rate has an appropriate response to anincrease in patient activity indicated by an activity sensor. In such acase, the second rule may include overriding the positive first ruledetermination. In some examples, the HF detection module 220 provides analert based on the declared HF event.

FIG. 3 shows a flow diagram of a method 300 to monitor HF of a subject.At block 305, a plurality of physiologic sensor signals are sensed usinga medical device and at least one sensor is implantable. Each sensorsignal is detected from a different sensor and includes physiologicalinformation. At block 310, the sensor signals are used to determinewhich physiological change events occurred (if any) of a set ofspecified physiological change events. At block 315, whether thedetected physiological change events are indicative of a change in HFstatus of the subject is determined using a first rule. At block 320,whether to override the first rule HF determination is determined usinga second rule. At block 325, whether a change in HF status occurred isdeclared according to the first and second rules.

Table 1 shows an example of sensor fusion to determine a change in HFstatus. Four sensors are included the example: a heart sound sensor todetect the S3 heart sound, an ITTI sensor, a respiration sensor, andphysiological response to activity (PRA) sensor. Binary logic is used todetermine the indication from an individual sensor. For example, asensor is deemed to indicate HF (“Y”) if the sensor output satisfies athreshold condition for indicating HF, and is deemed to not indicate RF(“N”) otherwise.

TABLE 1 S3 ITTI Resp PRA Alert Exceptions 1 Y Y Y Y Y 2 Y Y Y N Y S3high spec overrides PRA 3 Y Y N Y Y 4 Y Y N N Y 5 Y N Y Y Y 6 Y N Y N YS3 high spec overrides PRA 7 Y N N Y Y 8 Y N N N N 9 N Y Y Y Y 10 N Y YN N PRA high NPV overrides 11 N Y N Y Y 12 N Y N N N 13 N N Y Y Y 14 N NY N N 15 N N N Y N 16 N N N N N

As an illustrative example, the heart sensor (e.g., an accelerometer) isdeemed to indicate worsening HF when the heart sound sensor signalindicates an S3 heart sound having an amplitude greater than a threshold(e.g., 5 mg (acceleration in g's) or 15 mg), and a change in theamplitude of 100% (e.g., doubling). The ITTI sensor is deemed toindicate worsening HF when the impedance sensor signal changes bygreater than 10%. The respiration sensor is deemed to indicate worseningHF when the respiration sensor signal indicates a change in thedetermined respiration rate of greater than 5 breaths per minute, orwhen the determined respiration rate exceeds 30 breaths per minute. ThePRA sensor is deemed to indicate worsening HF when the sensor signal orsignals indicate the patient's response to physical activity hasincreased by more than 20%, or when a normalized ratio of breathingvolume (e.g., minute volume) to activity exceeds a threshold ratiovalue.

A majority rule is used to determine whether a change in HF statusoccurred and an alert should be generated. Normally, when the outputs ofat least two sensors satisfy the threshold condition, the alert isgenerated. This would be an example of an alert generated by the firstrule. However, as indicated in the table, there are exceptions that mayoverride the majority rule. Line 10 of the table would normally generatean alert due to the ITTI sensor and the respiration sensor indication achange in HF. However, a negative indication from the PRA sensor hassuch strong negative predictor value (NPV) that the negative PRAindication overrides the majority rule. This is an example of a secondHF rule (PRA's NPV) overriding a first HF rule (the majority rule).

A change in the S3 heart sound that satisfies the threshold criterionindicates worsening HF with high specificity. The S3 heart sound hassuch strong positive predictor value (PPV) that the positive S3indication overrides a negative PRA indication (as shown in lines 2 and6 of Table 1).

FIG. 4 is a flow diagram of an example of a method 400 to determinewhether a change occurred in the status of HF of a subject. In themethod 400, binary decision making is applied to the sensor outputs. Atblock 405, it is determined whether the heart sound sensor signalprovides a positive indication of HF, such as an increase in S3 heartsound amplitude. If it does, at block 410 it is determined if anothersensor provides a positive indication of HF. If yes, an alert isgenerated at block 415; if not, no alert is indicated at block 420.

If no S3 heart sound is included in the sensor signal, it is determinedat block 425 whether the impedance sensor (e.g., ITTI) provides apositive indication of HF. If not, no alert is indicated at block 430.If the impedance sensor does provide a positive indication of HF, atblock 435 it is determined whether one of the respiration or the PRAsensor provides a positive indication of HF. If not, no alert isindicated as shown in block 440. If so, then an alert is generated atblock 415.

FIG. 5 is a flow diagram of an example of another method to determinewhether a change occurred in the status of HF of a subject. Again, themethod 500 applies binary or ternary decision making to the sensoroutputs. At block 505, it is determined whether the sensor outputssatisfy a basic, or first, sensor fusion condition rule for HF (e.g., amajority rule). If not, flow is directed to no alert at block 510. Ifthe basic condition is met, it is determined whether secondaryconditions exist that alter the basic sensor fusion condition output. Atblock 515, it is determined whether conditions exist to rule in a changein HF status, such as the sensor indications showing that the subject isdyspneic and that the subject exhibits an S3 heart sound. If a Rule Incondition is met, an alert is generated at 520. At block 525, it isdetermined whether conditions exist to rule out a change in HF andoverride the basic condition rule for HF, such as the subject beingdyspneic, but not exertional dyspneic. If no Rule Out condition is met,an alert is generated at block 520. If a Rule Out condition is met, flowis directed to no alert at block 510.

According to some examples, logic more detailed than binary can be usedto weight the output from an individual sensor. Table 2 shows anotherexample of sensor fusion to determine a change in HF status. Again, foursensors are shown in the example, a heart sound sensor, an ITTI sensor,a respiration sensor, and a PRA sensor. Ternary logic instead of binarylogic is used to determine the indication from an individual sensor.Instead of a simple positive or negative indication from the sensor, thephysiological change event detection module 215 weights the outputs ofthe sensor as low, medium, or high according to the sensor signal by acomparison to one or more thresholds. The HF detection module thenweights the strength of the indication of a change in HF using theweighted sensor outputs.

TABLE 2 S3 ITTI Resp PRA Alert Logic Exceptions H H H H Red 2 H H H H MRed 2 H H H H L Red 2 H S3 high spec overrides PRA high NPV H H M H Red2 H H H M M Red 2 H H H M L Red 2 H S3 high spec overrides PRA high NPVH H L H Red 2 H H H L M Red 2 H H H L L Red 2 H H M H H Red 2 H H M H MRed 2 H S3 high spec overrides PRA high NPV H M H L Red 2 H S3 high specoverrides PRA high NPV H M M H Red 2 H H M M M Red 1 H + 2 M H M M L Red1 H + 2 M S3 high spec overrides PRA high NPV H M L H Red 2 H H M L MRed 1 H + 2 M H M L L Yellow 1 H + 1 M H L H H Red 2 H H L H M Red 2 HS3 high spec overrides PRA high NPV H L H L Red 2 H S3 high specoverrides PRA high NPV H L M H Red 2 H H L M M Yellow 1 H + 1 M H L M LYellow 1 H + 1 M H L L H Red 2 H H L L M Yellow 1 H + 1 M H L L L Yellow1 H M H H H Red 2 H M H H M Yellow 2 H PRA high NPV overrides S3 highspec M H H L Yellow 2 H PRA high NPV overrides S3 high spec M H M H Red2 H M H M M Red 1 H + 2 M M H M L Yellow 1 H + 2 M PRA high NPVoverrides S3 high spec M H L H Red 2 H M H L M Red 1 H + 2 M M H L LYellow 1 H + 1 M M M H H Red 1 H + 2 M M M H M Yellow 1 H + 2 M PRA highNPV overrides S3 high spec M M H L Yellow 1 H + 2 M PRA high NPVoverrides S3 high spec M M M H Red 1 H + 2 M M M M M Red 3 M M M M L Red3 M M M L H Red 1 H + 2 M M M L M Red 3 M M M L L Yellow 2 M M L H HYellow 1 H + 1 M M L H M Yellow 1 H + 1 M M L H L Green 1 H + 1 M PRAhigh NPV rules M L M H Yellow 1 H + 1 M M L M M Yellow 2 M M L M L Green2 M PRA high NPV rules M L L H Yellow 1 H + 1 M M L L M Yellow 2 M M L LL Green 1 M L H H H Red 2 H L H H M Red 2 H L H H L Yellow 2 H PRA highNPV rules L H M H Red 2 H L H M M Yellow 1 H + 1 M L H M L Yellow 1 H +1 M L H L H Red 2 H L H L M Yellow 1 H + 1 M L H L L Yellow 1 H L M H HYellow 1 H + 1 M L M H M Green 1 H + 1 M PRA high NPV rules L M H LGreen 1 H + 1 M PRA high NPV rules L M M H Yellow 1 H + 1 M L M M MYellow 2 M L M M L Green 2 M PRA high NPV rules L M L H Yellow 1 H + 1 ML M L M Yellow 2 M L M L L Green 1 M L L H H Yellow 1 H L L H M GreenPRA high NPV PRA high NPV rules L L H L Green PRA high NPV PRA high NPVrules L L M H Yellow 1 H L L M M Green Resp not specific L L M L GreenResp not specific PRA high NPV rules L L L H Yellow 1 H L L L M GreenPRA not specific L L L L Green nothing to alert

Table 3 shows an example of indications for worsening heart failure fromeach sensor. The outputs of the sensors are quantified or binned intothree ranges indicating low, medium, or high indications. Finergradations can be implemented by adding additional bins or ranges. Inthe example, the heart sound sensor output is quantified according tothe measured amplitude of the S3 heart sound. The ITTI sensor output isquantified according to a change in measured impedance. The respirationsensor output is quantified according to a change in respirationmeasured as breaths per minute. The PRA sensor is quantified accordingto the change in the patient's PRA.

TABLE 3 Sensors High probability Medium probability Low probability S3Amplitude Amplitude change in Amplitude change > 150%, or the range of100-150% change < 100% Amplitude > 15 mg ITTI Impedance Impedance changein Impedance change > 15% the range 10-15% change < 10% Resp Rate Ratechange in the Rate change ≥ 8 bpm range of 4-8 bpm change < 4 bpm PRAPRA PRA change in the PRA change > 30% range of 15-30% change < 15%

In some examples, the outputs are weighted according to the likelihoodthat the sensor signal indicates worsening HF. When the outputs of thesensor are weighted, the HF detection module 220 applies the first ruleto the weighted physiological change events to blend the sensor outputsand determine a likelihood that the change in HF status.

In the example of Table 2, under the first isle there is a strong orhigh likelihood of worsening HF when i) two or more sensors indicate ahigh likelihood of HF, or ii) one sensor indicates high likelihood andtwo sensors indicate medium likelihood, or iii) three or more sensorsindicate medium likelihood. Table 2 shows that a Red Alert is indicatedwhen one of these conditions occurs. Thus the alert includes anindication of the likelihood that the change in HF status occurred, with“Red” being the strongest indication. There is a medium indication ofworsening HF when i) one sensor indicates a high likelihood of HF andone sensor indicates a medium likelihood, ii) one sensor indicates highlikelihood, or iii) two sensors indicate medium likelihood. Table 2shows that a Yellow Alert is indicated when one of these conditionsoccurs to indicate a medium likelihood of worsening HF. There is a lowindication of worsening when i) only one sensor indicates a mediumlikelihood and the other sensor indicate low likelihood, or iii) all thesensors indicate low likelihood. This logic of the first rule isexemplary and the logic can be adjusted according to physicianpreference or according to a patient's unique requirements.

The second rule may then override the determinations of the first rule.For example, a low indication from the PRA sensor may override a mediumindication of one or both of the ITTI sensor and the Respiration sensoras shown in line 69 of Table 2, or may override a high indication of theITTI sensor or the Respiration sensor, as shown in line 48 of Table 2.In another example, a medium or high indication of an S3 heart soundindicated by the heart sound sensor overrides a low indication of thePRA sensor as shown in line 15 of Table 2.

In some examples, the HF detection module 220 declares whether there isa high, medium, or low indication of worsening HF and provides the alertbased on the declared HF event. Thus, the HF detection module determinesa level of urgency of the alert according to the first and second rules.

The above described multi-sensor fusion logic enhances the positiveprediction of worsening HF by the array of diagnostic sensors includedin the device 200. Other sensors, either implantable or external, can beused in the device 200 in FIG. 2 to monitor for HF instead of, or inaddition to, those discussed previously. In some examples, the device200 includes an implantable cardiac pressure sensor to measure chamberpressure of the left ventricle. A decrease in chamber pressure may beindicative of worsening HF.

In an example, a pressure sensor is implanted in a coronary vessel todetermine left ventricle pressure by direct measurement of coronaryvessel pressure. A description of systems and methods that use such animplantable pressure sensor is found in Salo et al., U.S. Pat. No.6,666,826, entitled “Method and Apparatus for Measuring Left VentricularPressure,” filed Jan. 4, 2002, which is incorporated herein by referencein its entirety. Other cardiac pressure sensors examples include a rightventricle (RV) chamber pressure sensor, a pulmonary artery pressuresensor, and a left atrial chamber pressure sensor. A change in heartchamber pressure may also be evident in heart sounds, and therefore aheart sound sensor may be used to deduce a change in pressure.

In some examples, the sensors 210 include an implantable heart ratesensor. In certain example, the heart rate sensor includes thepreviously mentioned circuits and electrodes to sense an electrogramsignal representative of heart depolarizations. A heart sound sensor maybe used to sense heart rate as well, such as by measuring intervalsbetween S2 heart sounds for example.

In some examples, the sensors 210 include an implantable oxygensaturation sensor. An oxygen saturation sensor produces an electricalsensor signal proportional to the oxygen saturation of blood, whichcould be reduced with worsening due to inadequate gas exchange in thepresence of one or bath of pulmonary congestion and decreased oxygendelivery to tissues. An approach for using an implantable sensor tomeasure blood oxygen saturation levels is found in Thompson, U.S. Pat.No. 5,342,406, entitled “Oxygen Sensor Based Capture Detection for aPacer,” filed Oct. 7, 1992, which is incorporated herein by reference inits entirety.

In some examples, the sensors 210 include an implantable cardiactemperature sensor. In some examples, the implantable cardiactemperature sensor is included in a lead system implanted into thecoronary sinus of a patient. The implantable cardiac temperature sensormeasures the temperature of the blood returning through the coronarysinus after having passed through myocardial tissue. As a byproduct ofnormal cardiac function, the heart generates heat. This heat isextracted by the perfusing blood. The blood exits through the coronaryveins into the coronary sinus before passing into the right atrium andright ventricle. The blood is then pumped through the lungs where theexcess heat is removed and passed out of the body with the exhaled air.

The useful work (W_(u)) performed by the left ventricle relates to thevolume of blood moved through the ventricle, whereas the heat outputfrom the left ventricle is related to total work (W_(T)). The differencein temperature between blood entering the left ventricle and blood in acoronary vein is related to left ventricular work. An increase in W_(T),or cardiac temperature as a surrogate measurement, that is notaccompanied by other indications of increased activity or patientexertion may indicate a lowering of efficiency of a patient'shemodynamic system due to worsening HF.

An approach to sensing temperature within a coronary vein is found inSalo, Patent Application Publ. No. 2003/0125774, entitled “Method andApparatus for Monitoring Left Ventricular Work or Power,” filed Dec. 31,2001, which is incorporated herein by reference in its entirety.

In some examples, the sensors 210 include a blood flow sensor. Examplesof a blood flow sensor include a cardiac output sensor circuit or astroke volume sensor circuit. Examples of stroke volume sensing arediscussed in Salo et al., U.S. Pat. No. 4,686,987, “Biomedical MethodAnd Apparatus For Controlling The Administration Of Therapy To A PatientIn Response To Changes in Physiologic Demand,” filed Mar. 29, 1982, andin Hauck et al., U.S. Pat. No. 5,284,136, “Dual Indifferent ElectrodePacemaker,” filed May 13, 1991, which are incorporated herein byreference in their entirety.

In some examples, the sensors 210 and the processor 205 are included inan IMD based system. FIG. 6 is an illustration of a system 600 thatincludes an external device 630 used to program parameters of an IMD635. The external device 630 includes a programming interface such as adisplay 640 and/or a keyboard 645 or computer mouse. The external device630 communicates with the IMD 635 wirelessly. The IMD 635 communicatesthe alert to the external device 630 to present the alert to a user. Insome examples, the external device 630 communicates the level of urgencyof the alert to the user, such as by displaying a high, medium or lowalert as a Red, Yellow, or Green Alert respectively. In some examples,at least one sensor is external and communicates information to the IMD635 wirelessly.

FIG. 7 is an example of a system 700 to monitor for HF of a subject. Thesystem 700 includes a plurality of sensors 710A, 710B, 710C. Each of thesensors 710A, 710B, 710C provides a sensor signal that includesphysiological information. The sensors may include combinations of anyof the sensors described herein.

The system 700 also includes an IMD 735 that includes at least one ofthe sensors 710A. The IMD 735 includes a sampling circuit 750 to samplea sensor signal, such as to generate digital values to represent thesensor output. The IMD 735 also includes first communication circuit 755to communicate the sampled sensor signal to a second device.

The system further includes an external device 730. The external deviceincludes a second communication circuit 760, to communicate with the IMD735 wirelessly, and a processor 705. The processor 705 includes aphysiological change event detection module 715 and an HF detectionmodule 720. The IMD 735 communicates a sampled sensor signal to theexternal device 730. In some example, the sampled sensor signal iscommunicated to the external device 730 via a third device such as arepeater. The repeater is local to the IMD 735, such as by being in thesame room as the patient, allowing the external device 730 to be remotefrom the patient. The physiological change event detection module 715detects an event from a sensor signal provided by one or all of thesensors 710A, 710B, 710C, and determines whether a detected event isindicative of a change in HF status. The HF detection module declareswhether the change in HF status occurred according to the first andsecond rules.

A medical device system that includes a suite of sensors andmulti-sensor fusion logic to blend the sensor indications enhances thepositive prediction and detection of worsening HF.

The above detailed description includes references to the accompanyingdrawings, which form a part of the detailed description. The drawingsshow, by way of illustration, specific embodiments in which theinvention can be practiced. These embodiments are also referred toherein as “examples.” All publications, patents, and patent documentsreferred to in this document are incorporated by reference herein intheir entirety, as though individually incorporated by reference. In theevent of inconsistent usages between this document and those documentsso incorporated by reference, the usage in the incorporated reference(s)should be considered supplementary to that of this document; forirreconcilable inconsistencies, the usage in this document controls.

In this document, the terms “a” or “an” are used, as is common in patentdocuments, to include one or more than one, independent of any otherinstances or usages of “at least one” or “one or more.” In thisdocument, the term “or” is used to refer to a nonexclusive or, such that“A or B” includes “A but not B,” “B but not A,” and “A and B,” unlessotherwise indicated. In the appended claims, the terms “including” and“in which” are used as the plain-English equivalents of the respectiveterms “comprising” and “wherein.” Also, in the following claims, theterms “including” and “comprising” are open-ended, that is, a system,device, article, or process that includes elements in addition to thoselisted after such a term in a claim are still deemed to fall within thescope of that claim. Moreover, in the following claims, the terms“first,” “second,” and “third,” etc. are used merely as labels, and arenot intended to impose numerical requirements on their objects.

Method examples described herein can be machine or computer-implementedat least in part. Some examples can include a computer-readable mediumor machine-readable medium encoded with instructions operable toconfigure an electronic device to perform methods as described in theabove examples. An implementation of such methods can include code, suchas microcode, assembly language code, a higher-level language code, orthe like. Such code can include computer readable instructions forperforming various methods. The code can form portions of computerprogram products. Further, the code can be tangibly stored on one ormore volatile or non-volatile computer-readable media during executionor at other times. These computer-readable media can include, but arenot limited to, hard disks, removable magnetic disks, removable opticaldisks (e.g., compact disks and digital video disks), magnetic cassettes,memory cards or sticks, random access memories (RAM's), read onlymemories (ROM's), and the like.

The above description is intended to be illustrative, and notrestrictive. For example, the above-described examples (or one or moreaspects thereof) may be used in combination with each other. Otherembodiments can be used, such as by one of ordinary skill in the artupon reviewing the above description. The Abstract is provided to complywith 37 C.F.R. § 1.72(b), to allow the reader to quickly ascertain thenature of the technical disclosure. It is submitted with theunderstanding that it will not be used to interpret or limit the scopeor meaning of the claims. Also, in the above Detailed Description,various features may be grouped together to streamline the disclosure.This should not be interpreted as intending that an unclaimed disclosedfeature is essential to any claim. Rather, inventive subject matter maylie in less than all features of a particular disclosed embodiment.Thus, the following claims are hereby incorporated into the DetailedDescription, with each claim standing on its own as a separateembodiment. The scope of the invention should be determined withreference to the appended claims, along with the full scope ofequivalents to which such claims are entitled.

What is claimed is:
 1. A method comprising: sensing a plurality ofseparate physiologic sensor signals produced using a plurality ofsensors, wherein each sensor signal includes physiological information;detecting a physiological change event from a sensor signal; determiningwhether the detected physiological change events are indicative of achange in heart failure (HF) status using a first device-based ruleapplied to the physiological change events; determining whether to ruleout a positive first rule HF determination using a second device-basedrule applied to at least one of the physiological change events;generating an indication of whether the change in HF status occurredaccording to the first and second rules; and changing a patient therapyaccording to the generated indication.
 2. The method of claim 1,including: sampling the plurality of separate physiologic sensor signalsusing a first medical device; communicating the sampled physiologicalsensor signals from the first medical device to a second separatemedical device; and using the second medical device, detecting thephysiological change event from the sampled physiological sensor signalsand generating the indication of whether the change in HF statusoccurred.
 3. The method of claim 1, comparing a physiological sensorsignal of the plurality of separate physiologic sensor signals to aspecified threshold; assigning one indication of a plurality ofindications of occurrence of a physiological change event to thephysiological sensor signal according to the comparison; andaccumulating indications assigned to the plurality of separatephysiologic sensor signals; and determining whether the detectedphysiological change events are indicative of a change in HF statususing the accumulated indications.
 4. The method of claim 1, wherein thedetermining whether the detected physiological change events areindicative of a change in HF status using a first device-based ruleincludes determining whether the detected physiological change eventsare indicative of a change in HF status when a majority of a set ofdetectable physiological change events is detected.
 5. The method ofclaim 4, wherein the determining whether to rule out a positive firstrule HF determination using a second device-based rule includesoverriding a negative first rule HF determination according to aspecificity of a detected physiological change event; and overriding thepositive first rule HF determination according to a negative predictivevalue of a physiological change event.
 6. The method of claim 1, whereinthe determining whether the detected physiological change events areindicative of a change in HF status using a first device-based ruleincludes determining whether the detected physiological change eventsare indicative of a change in HF using an individual assessment of HFusing the physiological information provided by the sensor signal ofeach of the sensors.
 7. The method of claim 1, including producing abinary indication of occurrence a physiological change event using asensor signal from a sensor of the plurality of sensors, and applyingthe first rule and the second rule to binary indications produced by thephysiological change event detection module.
 8. The method of claim 1,including producing a ternary indication of occurrence a physiologicalchange event using a sensor signal from a sensor of the plurality ofsensors, and applying the first rule and the second rule to ternaryindications produced by the physiological change event detection module.9. The method of claim 1, wherein sensing a plurality of separatephysiologic sensor signals includes sensing one or more of an activitysignal and an electrocardiogram signal.
 10. The method of claim 1,wherein sensing a plurality of separate physiologic sensor signalsincludes sensing a heart sound signal using an implantable heart soundsensor.
 11. The method of claim 1, sensing a plurality of separatephysiologic sensor signals using a plurality of sensors includes sensinga physiologic sensor signal using one or more of: a blood pressuresensor; an oxygen saturation sensor; a blood flow sensor; and atemperature sensor.
 12. The method of claim 1, wherein sensing aplurality of separate physiologic sensor signals includes sensing usingone or more of an impedance signal and a respiration signal.
 13. Amedical device system comprising: a processor for receiving a pluralityof sensor signals, wherein the processor includes: a physiologicalchange event detection circuit configured to: detect a physiologicalchange event of a subject from a sensor signal; and produce anindication of occurrence of one or more physiological change events; anda heart failure (HF) detection circuit configured to: determine whetherthe detected physiological change events are indicative of a change inHF status using a first rule applied to the physiological change events;determine whether to rule out a positive first rule HF determinationusing a second rule applied to at least one of the physiological changeevents; and generate an indication of whether the change in HF statusoccurred according to the first and second rules.
 14. The medical devicesystem of claim 13, wherein the first rule includes indicating a changein HF status when a majority of a set of detectable physiological changeevents is detected.
 15. The medical device system of claim 14, whereinthe second rule includes: overriding a negative first rule HFdetermination according to a specificity of a detected physiologicalchange event; and overriding the positive first rule HF determinationaccording to a negative predictive value of a physiological changeevent.
 16. The medical device system of claim 13, wherein the first ruleincludes an individual assessment of HF using the physiologicalinformation provided by the sensor signal of each of the sensors. 17.The medical device system of claim 13, wherein the physiological changeevent detection module is configured to produce a binary indication ofoccurrence a physiological change event using a sensor signal from asensor of the plurality of sensors, and wherein HF detection module isconfigured to apply the first rule and the second rule to binaryindications produced by the physiological change event detection module.18. The medical device system of claim 13, wherein the physiologicalchange event detection module is configured to produce a ternaryindication of occurrence a physiological change event using a sensorsignal from a sensor of the plurality of sensors, and wherein HFdetection module is configured to apply the first rule and the secondrule to ternary indications produced by the physiological change eventdetection module.
 19. The medical device system of claim 13, including aplurality of sensors that provides the plurality of sensor signals tothe processor, each sensor configured to provide a sensor signal thatincludes physiological information.
 20. The medical device system ofclaim 19, wherein the plurality of sensors includes at least one of anactivity sensor and an electrocardiogram sensor.